Present drug-likeness filters in medicinal chemistry during the hit and lead optimization process: how far can they be simplified?

Mignani, Serge; Rodrigues, João; Tomás, Helena; Jalal, Rachid; Singh, Parvinder Pal; Majoral, Jean-Pierre; Vishwakarma, Ram A.

http://hdl.handle.net/10400.13/2436

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Abstract(s)

During the past decade, decreasing the attrition rate of drug development candidates reaching the market has become one of the major challenges in pharmaceutical research and drug development (R&D). To facilitate the decision-making process, and to increase the probability of rapidly finding and developing high-quality compounds, a variety of multiparametric guidelines, also known as rules and ligand efficiency (LE) metrics, have been developed. However, what are the 'best' descriptors and how far can we simplify these drug-likeness prediction tools in terms of the numerous, complex properties that they relate to?

Keywords

Drug design Drug discovery Pharmaceutical preparations Filters in medicinal chemistry . Faculdade de Ciências Exatas e da Engenharia Centro de Química da Madeira

URI

http://hdl.handle.net/10400.13/2436

Citation

Mignani, S., Rodrigues, J., Tomas, H., Jalal, R., Singh, P. P., Majoral, J. P., & Vishwakarma, R. A. (2018). Present drug-likeness filters in medicinal chemistry during the hit and lead optimization process: how far can they be simplified?. Drug discovery today, 23(3), 605-615.